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This paper presents a study on deployment of policy based quality of service management at the mobile network edge. The requirements of fifth generation (5G) services for high bandwidth, low latency, reliability and availability can be fulfilled by Multi-access Edge Computing (MEC) former Mobile Edge Computing, which distributes cloud capabilities in the Radio Access Network. The paper studies the MEC potential for monitoring of accumulated usage of network resources based on data traffic volume on per session or user basis, for application traffic detection and control, and for policy based control on subscriber spending limits. Typical use cases are considered to illustrate the benefits of distribution of core network functionality for policy and charging control at the network edge. Migration of policy and charging control functions from the core to the edge, and providing them using virtualization and service oriented techniques enables cost reduction, performance improvement and reduced energy consumption for devices with constrained resources. [ABSTRACT FROM AUTHOR]

The concept of Multi-access Edge Computing (MEC) is introduced with the intention to improve network performance and quality of experience for end users. MEC brings cloud capabilities at the network edge and thus it helps to reduce the latency, increases network efficiency and security, providing context and radio network information awareness for applications. The MEC deployment closer to the Radio Access Network (RAN) is the best way to receive radio network and location information, to manage the bandwidth, and to handle the user traffic. In this paper, we consider two MEC deployment scenarios in 5G and estimate the latency introduced by signaling. In one of the scenarios, the MEC platform is co-located with Centralized Unit of Cloud RAN deployment and MEC services and applications may share the same virtualized platform. In other scenario, the MEC platform is located at an aggregation point in RAN and serves a few bas station. The latency reduction in former scenario is due internal interface between base station and MEC platform. [ABSTRACT FROM AUTHOR]

Network slicing is one of the key features of fifth generation (5G) system. Network slice is a virtual network including Radio Access Network (RAN) and Core Network (CN). The most typical scenario of utilization of network slicing is the setup of multiple slices within a single operator in order to cope with different User Equipments (UE) and service requirements. In alternative scenario, network slicing may be provided as a service, i.e. network slices may be setup and modified by 3rd parties. Currently network slice selection function is defined as a part of CN. In this paper, an approach to provide assistance information about RAN part slice selection close to the end user is proposed. The Multi-access Edge Computing (MEC) technology which distributes cloud intelligence at the network edge is used. The approach is described by typical use cases illustrating the proposed functionality and data model, which provides applications with unified way to access and store data. The approach realizability is shown by modeling the resource state as seen by the application and network. [ABSTRACT FROM AUTHOR]

The growing content delivery traffic becomes a challenge for efficient usage of network resources. Optimal utilization of scarce radio resources may be achieved by deployment of cloud capabilities in the radio access network i.e. by deployment of Multi-access Edge Computing (MEC). In this paper, we propose RESTful application programming interfaces (API) that enable third party MEC applications to send messages to end user devices in a specific geographical area. Using the API, an authorized mobile edge application may send a broadcast message to the network; monitor the delivery status of a sent broadcast message; and receive notifications about the message delivery status. The proposed APIs are described by use cases illustrating their functionality, data model representing the resources, and broadcast delivery status models as seen by mobile edge application and MEC server. Both models are formally described and verified. [ABSTRACT FROM AUTHOR]

Multi-access Edge Computing (MEC) is a cloud technology that converges telecommunication and computing capabilities in radio access network. The research and standardization activities for enabling advanced mobile edge services are ongoing with diverse challenges yet to be met. A key area is the development of Application Programming Interfaces (API) that enable application to acquire mobile edge resources and simply and efficiently to manage them. Bandwidth Management Service (BWMS) is a mobile edge service that enables all registered applications to statically and/or dynamically register for specific bandwidth allocation per session/application, and to get information about the configured bandwidth allocation. The paper proposes an extension of BWMS that enables authorized applications to supervise establishment, modification and release of radio access bearers and thus to manage dynamically the available bandwidth under current radio conditions. The proposed extended functionality is illustrated by information flows, data models and actual API definition. As a proof of the concept, resource state models are provides, formally described and verified. [ABSTRACT FROM AUTHOR]